Over the past few months, LGND has hosted its first cohort of “summer fellows”. They come from all around the world and work on exciting projects spanning Earth data–from engineering to answering scientific questions and building impactful applications.

Over the coming months, they will show what they’ve built with LGND’s products and share their findings in blog posts. For now, let’s meet them in their own words:

Aalyaan Ali

I am a second-year at Brown University studying Applied Math + Computer Science, and Geophysics/Climate Physics. My interests lie in Earth systems, climate modeling, and AI, and my research experience spans applied machine learning projects in the geosciences and oceanography. At school, I’m involved in AI Safety, Environmental Health club, and serve as a violinist in the chamber orchestra. At LGND, I’ve been working on making Embeddings more explainable through notebooks and games. 

Taari Chandaria

I am a second-year student at Brown University studying Mathematics and Computer Science. I’m fascinated by how technology can be used to build transformative companies and spend much of my time working at the intersection of startups, engineering, and investing. At Brown, I am involved with Van Wickle Ventures, the university’s student-run VC fund, and run the Innovation Dojo startup incubator. Previously, I conducted particle physics research at CERN and worked as a technical intern at Finwave Semiconductor. In my free time, I enjoy playing the drums, trying out new restaurants, and reading. At LGND, I’ve been working on extending the capabilities of embeddings to more complicated change detection as well as integrating embeddings into agent harnesses.

Kinzah Cordeiro

I am a researcher interested in applying Earth science to address climate change challenges. I hold an MSc in Geoscience from University College London, where I focused on tectonics. My research experience spans deep mantle dynamics and geochemistry, with a focus on plate subduction and its role in the chemical and physical evolution of Earth’s mantle. Prior to LGND, I was a GIS engineer at 44.01. At LGND, I am working on a seismic impact mapper, which uses LGND's embeddings to detect unique geologic formations and minerals at the surface level.  Future work includes embedding Sentinel-1 InSAR data to measure sub-surface data, including ground deformation to visually identify high-impact zones.

Denis Groshev

I am currently studying Environmental Engineering with a focus on AI4EO at Technical University of Munich. I am particularly interested in vision foundation models for infrastructure monitoring and ML-assisted GEOINT. Previously, I worked as an intern at the Department of Safeguards at IAEA, and conducted research on applications of ML in South Korea, Austria and Germany. In my free time, I enjoy travelling, photography and anything in between. At LGND, I am working on a geospatial intelligence framework that fuses regulatory filing data, web and news scraping, and LGND embeddings to monitor construction and mining project lifecycles worldwide. 

Sawssen Hannachi

I recently graduated with a Master’s of Research in Data Science and Information Retrieval from the University of Manouba. My research focuses on Neurosymbolic AI particularly graph neural networks and ontology for remote sensing image analysis. Continuing this focus at LGND, I am building the company’s comprehensive ontology giving structure and meaning to the concepts our models learn from space, and how these concepts are searched and evaluated. I am also testing the capabilities of LGND embeddings ranging from proof of concepts for brine seep and copper exploration to scouting ideal sites for wind turbine installations. Outside of work, I enjoy being surrounded by nature and spend my weekends volunteering at a farm in Takelsa. 

Rashid Mahmood

I am an undergraduate student at the University of Toronto, studying Electrical and Computer Engineering. I am interested in using Mathematics, Software, and Technology in general to work on causes that are impactful. In my free time, I like going on long walks, hanging out with friends, meeting new people, and trying out Shawarma places in Toronto! My work at LGND so far has been building projects on top of the embeddings-api - mainly focusing on interactive maps for exploring visual symmetry.

Deepa Rangarajan

I am from New Delhi, India and a recent Master of Science (MS) graduate from Cornell University. After majoring in computer science during my bachelors, I joined the firm Goldman Sachs as a technology analyst. However, when building software for investment bankers wasn’t giving me gratification, I gauged my innate desires and realized that I wanted to help solve environment and sustainability challenges. Hence, I uprooted my entire life to pursue an interdisciplinary graduate program at Cornell, where I got to learn about multiple artificial intelligence frameworks and satellite data technologies, while applying them to agronomy and terrestrial ecosystems. I also learned the nuances of conducting successful research, which I presented through my thesis titled, “Characterizing space-time transitions to resilient wheat in Eastern India using remote sensing and deep learning”. I am very excited to further pursue my interests and join LGND AI as a summer fellow as I will get access to work with sophisticated geospatial AI technology and apply them towards my passion for understanding and mitigating climate change, while having the mentorship of some of the top researchers of the field.

Sebastian Ricke

I'm passionate about leveraging AI to address environmental challenges. I spent a couple of years at an AI research center working on translation models for low-resource indigenous languages. More recently, my research has shifted toward geospatial foundation models at the University of Colorado Boulder. At LGND, I've been working on uncovering the inner structure of our text-image embedding space to improve search and guide future model development. In my free time, I enjoy spending time outdoors as well as reading history books and practicing yoga.

John Paul Sosnitsky

I am a rising second-year student at Brown University studying Applied Mathematics. At Brown, I pursue my curiosity about tech and investing through Van Wickle Ventures, the university’s student-led venture fund, with a specific interest in how recent advancements in geospatial data can drive economic growth. At LGND, I have been working on a lithium field detector in South America, helping the engineering team with live Sentinel2 image ingestion, and also chipping in with GTM work such as drafting proposals. I also love playing soccer and Settlers of Catan, reading, and demolishing my friends in fantasy football.

Dingqi Ye

I am a Ph.D. student in Geography & GIS at the University of Illinois Urbana-Champaign, working on remote sensing foundation models, machine learning, and geospatial AI. My research focuses on developing reproducible and reliable methods for analyzing remote sensing foundation model representations under spatiotemporal and sensor shifts, with applications in Earth observation tasks. My work at LGND primarily involved embedding generation and quality evaluation, while also contributing to the quality evaluation of VLM-generated captions. Outside of work, I like music. I play the guitar and enjoy tinkering with just about anything that makes a sound.